Publication Date: 2023/11/28
Abstract: Enhancing communication efficiency and dependability in multiple input/multiple output systems (MIMO) is largely dependent on channel estimation. Two popular methods for calculating mean square error (MMSE) and zero forcing (ZF) are obtaining precise channel estimation. By creating an inverted channel matrix, the Zero Forcing method seeks to neutralize interference and essentially eliminate the influence of inter-symbol interference. Though it may be susceptible to errors and noise, this approach is computationally efficient. On the other hand, the aim of lowest mean square error channel estimating is to minimize the mean square error between the estimated and actual channels. keeping in mind both noise and interference. This technique provides improved robustness compared to ZF, especially in challenging signal conditions. Both ZF and MMSE techniques contribute significantly to the advancements of MIMO systems, with each method presenting its own advantages and trade-offs. The choice of channel estimation method depends on specific application requirements, computational complexity considerations, and the prevailing signal environment. Accurate channel estimates are crucial for optimizing data rates and ensuring reliable communication in MIMO Systems.
Keywords: Bit error rate (BER), Rayleigh Channels, Zero Forcing (ZF), Multiple Input Multiple Output Systems (MIMO), Signal to Noise Ratio (SNR), Binary Phase Shift Keying (BPSK), and Minimum Mean Square Error Method (MMSE).
DOI: https://doi.org/10.5281/zenodo.10212388
PDF: https://ijirst.demo4.arinfotech.co/assets/upload/files/IJISRT23NOV796.pdf
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